/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
 *
 *=========================================================================*/
#ifndef itkNormalizeImageFilter_hxx
#define itkNormalizeImageFilter_hxx

#include "itkImageRegionIterator.h"
#include "itkProgressAccumulator.h"

namespace itk
{
template <typename TInputImage, typename TOutputImage>
NormalizeImageFilter<TInputImage, TOutputImage>::NormalizeImageFilter()
{
  m_StatisticsFilter = nullptr;
  m_StatisticsFilter = StatisticsImageFilter<TInputImage>::New();
  m_ShiftScaleFilter = ShiftScaleImageFilter<TInputImage, TOutputImage>::New();
}

template <typename TInputImage, typename TOutputImage>
void
NormalizeImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
  Superclass::GenerateInputRequestedRegion();
  if (this->GetInput())
  {
    const InputImagePointer image = const_cast<typename Superclass::InputImageType *>(this->GetInput());
    image->SetRequestedRegionToLargestPossibleRegion();
  }
}

template <typename TInputImage, typename TOutputImage>
void
NormalizeImageFilter<TInputImage, TOutputImage>::Modified() const
{
  Superclass::Modified();
  m_StatisticsFilter->Modified();
  m_ShiftScaleFilter->Modified();
}

template <typename TInputImage, typename TOutputImage>
void
NormalizeImageFilter<TInputImage, TOutputImage>::GenerateData()
{
  auto progress = ProgressAccumulator::New();

  progress->SetMiniPipelineFilter(this);

  progress->RegisterInternalFilter(m_StatisticsFilter, .5f);
  progress->RegisterInternalFilter(m_ShiftScaleFilter, .5f);

  // Gather statistics

  auto localInput = TInputImage::New();
  localInput->Graft(this->GetInput());

  m_StatisticsFilter->SetInput(localInput);
  m_StatisticsFilter->Update();

  // Set the parameters for Shift
  m_ShiftScaleFilter->SetShift(-m_StatisticsFilter->GetMean());
  m_ShiftScaleFilter->SetScale(NumericTraits<typename StatisticsImageFilter<TInputImage>::RealType>::OneValue() /
                               m_StatisticsFilter->GetSigma());
  m_ShiftScaleFilter->SetInput(localInput);

  m_ShiftScaleFilter->GraftOutput(this->GetOutput());
  m_ShiftScaleFilter->Update();

  // Graft the mini pipeline output to this filters output
  this->GraftOutput(m_ShiftScaleFilter->GetOutput());
}
} // end namespace itk

#endif
